A. Technical Field of Field of the Invention
The present invention relates to a method for testing and predicting failures of an electronic system, and more particularly, to a method that provides a knowledge base based on human expertise and comprising digraph models all used for analyzing faults in complex systems.
B. Description of the Prior Art
Reliability models are commonly derived during the inception of an electronic system, especially if such an electronic system is complex and susceptive to having a single failure render the system inoperative. Reliability models take into account various parameters, such as the failure rate of the individual components and the interrelationship of the components making up the system. The reliability models are commonly implemented to be used in failure mode analysis of systems and one such usage described in U.S. Pat. No. 5,014,220, of C. M. McMann, herein incorporated by reference.
Reliability analysis, such as failure mode effects analysis (FMEA), fault tree or digraphs analysis, are performed on many systems during their inception stage. Digraph analysis normally consists of digraph models which comprises AND/OR directed graphs with nodes, connected by directed edges, representing hardware failures, human actions, modes of operation, and other factors affecting system operation. The reliability analysis contained in these digraph models, derived during the inception stage of the complex system, comprises a wealth of information that can be used to help build automatic diagnostic systems that service complex electronic systems. A significant amount of effort can be saved by using reliability analysis information inherent in the digraph models to build a diagnostic system since much of the knowledge or human expertise required for diagnosing a system failure has already been derived to develop the reliability-analysis models.
Digraph models used in reliability analysis have many benefits, one of which is that the models can be derived from system schematics in a fairly straightforward manner by associating a digraph node with each component in the schematic, adding directed edges to represent physically connections between components, and augmenting the basic digraph model with knowledge about component failure modes and rates, and other system design considerations, such as fault tolerant features provided by redundant components or duplicate subsystems. A further discussion of digraph modeling may be found in the technical article entitled Digraph Matrix Analysis of Ivan J. Sacks, published in the IEEE Transactions on Reliability, Vol. R-34, No. 5, pp. 437-445, December, 1985. A still further discussion of digraph modeling is described in the technical article entitled Automatic Translation of Digraph to Fault-Tree Models of D. L. Iverson, published in the Proceedings of the Annual Reliability and Maintainability Symposium of the IEEE, New York-Las Vegas, Nev., USA, January, 1992, pp. 354-362.
Although the digraph models serve well their intended function in reliability analysis, as well as being used in diagnostic fault isolation techniques, digraph modeling applications are somewhat limited when the associated nodes (possible failures) in a sophisticated system being analyzed, reaches into the thousands, e.g., greater than 1,000. For example, using the computing techniques described in the above two technical articles of Sachs and Iverson, when the system involves nodes of about 1100, about 3400, and about 7000, the processing time involved with computer workstations yielding a solution of the related digraph models respectively is about 12 minutes, 42 hours, and four days. It is desired that means be provided to allow digraph models to be used for reliability and diagnostic analysis of complex electronic systems, yet provide a solution therefor within a relatively short operational time, such as seconds or minutes and not hours and days.
Accordingly, it is a principal object of the present invention to provide reliability and diagnostic analysis using digraph models and unique techniques and, more importantly, to a method which substantially reduces the time required to derive a solution thereof.
It is another object of the present invention to provide digraph techniques which incorporate human expertise so as to derive a knowledge base that can be used for various artificial intelligent applications to solve associated problems.
A further object of the present invention is to provide a knowledge base incorporating digraph models and techniques that may be used to provide solutions that may be graphically displayed to a user or provided by way of a printout.